DocumentCode :
714505
Title :
Increasing the performance of face recognition in near infrared region with Hierarchical Grouping
Author :
Yildiz, Huseyin ; Torunoglu, Osman ; Saraydemir, Safak
Author_Institution :
Elektrik ve Elektron. Muhendisligi Bolumu, Kara Harp Okulu, Ankara, Turkey
fYear :
2015
fDate :
16-19 May 2015
Firstpage :
1284
Lastpage :
1287
Abstract :
In this study, a new method is proposed to increase the performance for near infrared region(NIR) face recognition problem. this method is named as Hierarchical Grouping (HG). Principal Component Analysis (PCA) and Local Binary Pattern (LBP) methods which are widely used in literature, are used for feature extraction and for classification k Nearest Neighbor (kNN) method is used. The developed algorithm is tested on CBSR NIR database. Performance increase is obtained for the different preprocessed database by using hierarchical grouping method.
Keywords :
face recognition; feature extraction; image classification; principal component analysis; visual databases; CBSR NIR database; LBP method; NIR face recognition; PCA; feature extraction; hierarchical grouping method; k nearest neighbor method; kNN method; local binary pattern methods; near infrared region; principal component analysis; Biomedical imaging; Computer vision; Conferences; Databases; Face; Face recognition; Principal component analysis; LBP; NIR; PCA; face recognition; hierarchical grouping; kNN;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2015 23th
Conference_Location :
Malatya
Type :
conf
DOI :
10.1109/SIU.2015.7130073
Filename :
7130073
Link To Document :
بازگشت